Source: City of Lahti
4. Indicators for assessing urban segregation and social inclusion
The importance of indicators is emphasised in many of the Nordic countries’ policies aimed at enhancing social inclusion and counteracting segregation. The focus of this chapter is therefore on the role of indicators in supporting policy and planning towards more socially inclusive cities across all the Nordic countries.
Having first detailed the relevant national-level indicators already in existence or in development, as well as how data, indicators and research-based knowledge is addressed in national policies, the chapter hones in on the city level: specifically Helsinki (Finland), Odense (Denmark), Oslo (Norway), Örebro (Sweden) and Reykjavík (Iceland). Throughout, a key focus is on exploring what the governance of indicators looks like at different territorial levels, including which actors are involved in collecting and assessing the relevant data, and in using it to support policy and planning measures.
More specifically, the following overarching questions are addressed:
- What role do indicators play in supporting policy and planning towards more inclusive cities, both at national level and in different cities?
- How, to what extent, and by whom are these indicators used to support policies and strategies at the national, city and neighbourhood level?
- What benefits and opportunities – and conversely risks and challenges – do the indicators present?
4.1 Finland
Several of Finland’s national policies dealing with segregation and social inclusion place stress on the role played by data and indicators, as well as the importance of research-based knowledge in supporting policy-making and planning. For example, the former government’s programme Inclusive and Competent Finland (Finnish Government, 2019), launched in 2019, pledged to make policy-making more knowledge-based, reliant on systematic impact assessments, and founded on deeper cooperation with the scientific community. Building on this, the need for a range of indicators, assessments and research in support of the programme’s objective of strengthening participation and trust, while reducing social exclusion, was highlighted.
Similarly, the Regional Development Decision 2020–2023, which specified the government’s regional policy priorities, placed strong emphasis on indicators (Ministry of Economic Affairs and Employment, 2020b). Promoting inclusion and wellbeing while preventing inequality was one of the programme’s six key priorities, and towards this end the Finnish regions were tasked with using effective tools for monitoring, preventing and reducing inequality.
In addition, the national Urban Programme 2018–2022 highlighted the importance of a common knowledge base for setting and monitoring shared planning targets, stressing that cities need up-to-date information on the wellbeing of various population groups across different territories (Ministry of Finance, 2020).
Meanwhile, the Neighbourhood Renewal Programme 2020–2022 targeted suburban housing estates, with a key strategic focus being the use of data and knowledge-based decision-making in the prevention of segregation (Nevalainen, 2021). The programme provided funding to cities carrying out development projects in selected neighbourhoods, and also funded numerous research projects dealing with housing estates and segregation.
4.1.1 From fragmented local monitoring towards more harmonised national segregation indicators?
The above-mentioned examples demonstrate the increased societal importance ascribed to social sustainability, inclusion and segregation in Finland’s cities, and consequently the strong emphasis placed on using knowledge, data and indicators to support planning and policy work in relevant national policies. Even so, when it comes to monitoring segregation or social inclusion in cities across Finland, no common indicators currently exist. This is perhaps surprising given Finland generally enjoys a high standard of national indicators and statistics, which are well developed in many thematic areas.
One interviewee for this study suggested the absence of relevant indicators was largely due to the relatively recent emergence of urban segregation as an important societal issue in Finland (Interview 4, 2023). For a long time, the prevailing sentiment was that the country’s key territorial disparities existed between different regions and municipalities, meaning the monitoring of territorial differences has to date largely been carried out at this level. Recent years, however, have seen more widespread acknowledgement that urban segregation should be monitored at both a national and more granular level, in order to capture socio-spatial differences between neighbourhoods and local areas (Interview 4, 2023).
While it is only recently that the imperative of monitoring segregation at the national level has emerged, some municipalities have long used various indicators to systematically follow-up on segregation. This is especially the case for the City of Helsinki, examined in the next section, but can also be seen in, for instance, the Tampere region and the City of Lahti, where segregation has been monitored in order to support policy-making and planning (see Box 1). A more thorough examination of the City of Tampere and City of Lahti can be found in sections 5.1 and 6.1 respectively.
Box 1. Monitoring segregation in Tampere and Lahti
- The City of Tampere’s model for monitoring segregation has recently been upscaled to the wider Tampere region in order to shed light on and prevalence of segregation and the factors driving it. A 2020 report broke down segregation across the region based on a wellbeing index, constructed using grid-level data (250 × 250 m) on unemployment rates, educational levels and income levels from different years (1995, 2005, 2015, 2017) (Hynynen, 2020). The results have been used, for example, in supporting regional housing policy and welfare service planning (Sustainable City, n.d.).
- The City of Lahti has made the systematic use of data and indicators when monitoring development of the city and its different areas a core governance principle. In preparing the city’s 2023‒2028 housing and land use policy, data was employed to analyse segregation patterns and trends across the city (Kangas, 2021). This involved a socio-economic index based on grid-level data (250 × 250 m) on income levels, educational levels and unemployment (City of Lahti, 2023a), calculated for the years 2000, 2010 and 2019. Inspiration has been drawn from the methods employed in Helsinki and Tampere (City of Lahti, 2024).
From a national policy perspective, the fact that certain large municipalities have created their own indicators and monitoring systems – often independently of each other – has led to the field becoming somewhat fragmented. At the same time, most of the other Finnish municipalities lack such data and indicators in their work. This is especially the case for smaller municipalities, which often lack the resources and expertise necessary to conduct this type of monitoring. Consequently, little is known about segregation trends outside Finland’s largest urban regions (Interview 4, 2023).
Against this backdrop, in 2020 the Urban Policy Committee
The Urban Policy Committee consists of representatives from various ministries and cities, as well as the Association of Finnish Local and Regional Authorities, and is tasked with supporting implementation of national urban policy during a given government’s term, including strengthening cooperation between different levels of governance (Ministry of the Economic Affairs and Employment, n.d.).
The Finnish Environment Institute (SYKE) has been tasked with taking the lead in developing national segregation indicators as part of MAL monitoring. According to a report presenting key considerations for this work, the indicators will be calculated at the sub-municipal level – while the exact territorial unit is not specified, postal code areas are mentioned as a possibility (Tiitu et al., 2023). Nevertheless, the intention is for the indicators to be presented at a more generalised territorial level, such as for municipalities as a whole, rather than openly providing monitoring data for individual neighbourhoods.
The MAL agreements concern Finland’s largest urban regions. As such, the initial indicators have been developed for the regions signed up to these agreements (Helsinki, Tampere, Turku, Oulu, Jyväskylä, Kuopio, Lahti). Nevertheless, the indicators could relatively easily be upscaled to cover other regions, or even the whole country. The indicators will build on data from the Building and Housing Register (RHR), as well as the YKR monitoring system of spatial structure and urban form, with key variables set to include educational level among the employed population, unemployment rate, disposable monetary income, proportion of foreign-language speakers, and proportion of rental housing (Tiitu et al., 2023). At the time of writing, however, it remains unclear what role these indicators will actually serve in supporting policy and planning interventions.
4.1.2 Counteracting segregation as a strategic goal in the City of Helsinki
Among Finnish cities, segregation has undoubtedly been most prominent on the policy agenda in Helsinki. Various studies have drawn attention to the growing segregation seen in Helsinki since the severe economic recession of the early 1990s, with socio-spatial differences subsequently becoming more pronounced during the 2000s (Kortteinen et al., 2006; Kortteinen & Vaattovaara, 2015; Vaattovaara et al., 2011; Varady & Schulman, 2007).
Such issues were clearly expressed in a report produced by the City of Helsinki in 2019, which stated that while segregation is generally not severe, worrying signs are present (City of Helsinki, 2019). According to the report, while no part of the city has deteriorated in absolute terms, the most affluent areas have become increasingly well-off, while deprivation has become more multilayered and concentrated in other areas.
Raised concerns about segregation have also been driven by developments in neighbouring countries, particularly Sweden and Denmark. In this respect, the city administration has expressed interest in learning more about the potential problems posed by segregation, and how best to prevent them becoming overly severe (Interview 3, 2022).
Several of the 13 priorities set out in the current Helsinki City Strategy, which covers the years 2021–2025, have a focus on counteracting segregation (City of Helsinki, 2021a). According to the strategy, Helsinki aims to be a city where widening polarisation between districts is prevented and residents of every neighbourhood can live a safe, pleasant life. Towards this end, the strategy states that Helsinki will practice positive discrimination and combat segregation across all its activities, from housing policy and spatial planning to social work and education, to culture and leisure.
Here, the role of high-quality early childhood education in balancing out socio-economic differences between children, together with urban culture and investments in parks, playgrounds and sports facilities, are highlighted as key enablers for a good life across neighbourhoods. In addition, one of the four strategic objectives in the 2020 Implementation Programme on Housing and Related Land Use (City of Helsinki, 2021b, 2021c) concerns neighbourhood vitality and preventing segregation.
A key policy approach for counteracting segregation, which has been applied by the City of Helsinki since the 1970s, is social mixing (Ronkainen & Eskelä, 2022). This involves mixing different housing tenure forms in neighbourhoods in the planning and construction phase, with the aim of ensuring that the housing stock is not limited to social rented housing (e.g. Kemppainen 2017). Successfully pursuing this strategy has not only required a city planning monopoly, but strong land ownership on the part of the city authorities in terms of conveying housing plots (Ronkainen & Eskelä, 2022). While this policy has not prevented the emergence of segregation altogether, it does seem to have slowed down and mitigated the growth of spatial disparities between neighbourhoods (Vaattovaara et al., 2018; Vilkama et al., 2023).
Figure 8. Construction in Kalasatama, a new waterfront area being developed in Helsinki
Source: City of Helsinki, Jussi Hellsten
Another important approach has been the City of Helsinki’s Neighbourhood Project (lähiöprojekti), which includes earmarked funding for developing certain suburban neighbourhoods deemed to be less well-off (City of Helsinki, 2016a). The project was originally launched in 1996 to alleviate the consequences of the 1990s recession, when several suburban areas in the eastern parts of the city became associated with high unemployment, social problems and exclusion (City of Helsinki, 2016b; Salmela, 2014). More recently, the neighbourhood project model was revisited in connection with a major reorganisation of the city and a desire to find new ways of working. The new area-based model known as the Suburban Regeneration Model (kaupunkiuudistus) aims to prevent segregation and improve the liveability and appeal of residential areas in a comprehensive way, using infill construction as a key tool (City of Helsinki, 2021c). The new model is based on more cross-sectoral ways of working, with various long-term measures and investments targeted at specific suburban areas (Interview 3, 2022).
The adoption of the new approach coincided with the creation of Helsinki’s new Participation and Interaction Model (osallisuus- ja vuorovaikutusmalli) (City of Helsinki, n.d.-d), which is partly operationalised through so-called ‘borough liaisons’ (stadiluotsi). These operatives are city employees who work in residential areas and seek to strengthen the inclusion of local residents. Thus, beyond simply counteracting segregation, the issue of social inclusion has also grown increasingly important and is now tied to the City of Helsinki’s objectives concerning segregation (Interview 3, 2022).
When it comes to counteracting segregation, a key challenge mentioned by interviewees is that the City of Helsinki is a very large organisation (Interview 3, 2022). This means different entities within the city organisation are tasked with carrying out a variety of different measures, resulting in a somewhat fragmented approach that often lacks overall coordination. In acknowledgement of this, new strategic programme groups were set up when the new mayor entered office in 2021, including a segregation programme group that aims to improve coordination between different branches of the city administration.
4.1.3 The role of indicators in supporting the City of Helsinki’s policy and planning
The City of Helsinki has a long tradition of using research and data to support its planning and policy-making, with the city’s first statistics unit established way back in 1911 (Cantell & Lahti, 2011). Today, the Executive Office’s Urban Research and Statistics Unit conducts research, maintains official statistics, registers data, produces statistical publications, and provides relevant information services (City of Helsinki, n.d.-g).
Alongside this, several other city administration units gather and maintain indicators for specific purposes. More generally, data and indictors are used by different administrative branches in various ways.
Box 2. Examples of openly available statistical data from the City of Helsinki
The City of Helsinki’s Urban Research and Statistics Unit maintains various
statistical databases , most of which can be accessed openly and free of charge. Key
databases include:
statistical databases , most of which can be accessed openly and free of charge. Key
databases include:
- Aluesarjat, which contains statistical time series data for the City of Helsinki and its wider region on a variety of phenomena, including population structure; development and projections; household structure; income; education; labour market and employment; and the built environment and housing stock. The database is updated regularly (monthly, quarterly or annually depending on the data), with the longest time series ranging back to 1962. Data can be obtained for the entire region at the municipality or district level, while more spatially detailed neighbourhood-level data exists for the cities of Helsinki, Espoo and Vantaa.
- The Wellbeing Statistics database contains time series data on the wellbeing of children and young people in Helsinki, including in the areas of population and living conditions; education and school conditions; work and employment; health and lifestyles; social relations; leisure; and security. Subdistricts are most detailed spatial level for which data is available.
When it comes to addressing segregation, indicators are used for determining which districts will be subject to area-based interventions as part of the Suburban Regeneration Model. Areas are selected based on data concerning socio-economic characteristics, housing stock, service structure and rail transport connectivity (City of Helsinki, n.d.-e). Here, the objective is to identify areas that are socio-economically disadvantaged; where the built environment requires significant refurbishment; and where housing stock mainly consists of rental housing – in other words, areas where regeneration efforts aimed at enhancing neighbourhood vitality are most needed.
One method deployed by the City of Helsinki to tackle school segregation is providing so-called ‘needs-based funding’ (tarveperusteinen rahoitus) to those comprehensive schools in greatest need of support (Ramos Lobato, 2023). This approach relies heavily on data, with funds distributed according to a calculation model that uses key variables associated with learning outcomes, specifically the proportion of: 1) households with a parent with tertiary education; 2) households with an unemployed parent; 3) households in the lowest income quintile; and 4) students with a foreign language registered as their first language. This model helps predict learning outcomes and captures neighbourhood differences in the educational wellbeing challenges faced by schools (Oittinen et al., 2023).
Interviewees also pointed to the nationwide ‘School Health Promotion Study’ (Kouluterveyskysely) as an important source of data for tackling segregation (Interview 3, 2022). The Finnish Institute for Health and Welfare (THL) has conducted the study every second year since 1996 in order to monitor the wellbeing, health and school results of the country’s children and adolescents (THL, 2024). The data concerning Helsinki provides valuable background information on neighbourhood-level differences in wellbeing from a children and youth perspective (Interview 3, 2022).
Another priority highlighted in the Helsinki City Strategy 2021–2025 is strengthening residents’ sense of security (City of Helsinki, 2021a). An important data source in monitoring progress towards this goal is the Helsinki Safety Survey, which has been conducted every third year since 2003 (City of Helsinki, n.d.-a). The survey captures the experiences and views of Helsinki residents aged 15–79 on the city’s safety and security situation in both the wider city and their own neighbourhood. Other important data sources on this subject include police reports and qualitative observations received from those working on the ground in neighbourhoods, which are important for assessing the security situation across different parts of the city – for instance regarding street gangs, which have been a growing concern in recent years (Interview 3, 2022).
While Helsinki has a long history of using qualitative and/or quantitative data and indicators, interviewees were keen to point out that their importance has grown (Interview 3, 2022). The 2021–2025 city strategy includes 13 priority areas, each of which is monitored using 2–8 indicators. The ‘Cultivating safe neighbourhoods with distinctive identities’ priority area, for instance, has a strong focus on counteracting segregation and ensuring people can live a safe, pleasant life in all neighbourhoods. Here, three main indicators are used to monitor progress: 1) a socio-economic sum index, based on the proportion of residents with a low income, no job and/or a low educational level in a given area; 2) how pleasant residents perceive their area of residence to be; and 3) the share of owner-occupied and right-of-occupancy dwellings in areas where housing stock is primarily renter-occupied. More generally, the use of data and indicators to support policy work and planning is directly reflected in the priority area stating that data and digitalisation will be used to help run a smart city (City of Helsinki, n.d.-b).
Furthermore, indicators are central to monitoring Helsinki’s progress towards the Sustainable Development Goals (SDGs). In total, more than 60 indicators are used to follow the city’s progress in meeting the 17 goals. For instance, reduced segregation is explicitly stated as a key goal in relation to SDG 10 (reduced inequalities), (City of Helsinki, n.d.-f), with four main indicators used to monitor progress: 1) Gini coefficient (index of relative income inequality); 2 NEET share (Not in Employment, Education or Training), 20–24-year-olds; 3) segregation by educational background; and 4) segregation by ethnic background (City of Helsinki, n.d.-c).
4.1.4 Overcoming challenges with linking indicators to policy and planning
A key interest of this chapter is better understanding how data and indicators can support policy and planning, including what the main advantages and challenges are. In this respect, interviewees emphasised the City of Helsinki’s established traditions of using data and research to support policy and planning, and moreover that counteracting segregation has been a clear political priority addressed by a range of preventive measures over the years (Interview 3, 2022). Important in this context is the broad support given by Finland’s political parties to addressing segregation – while views on the exact measures to be implemented may vary, there is general agreement on the need to deal with the issues faced.
Interviewees also highlighted the research conducted on segregation in Helsinki and its wider region over recent decades. In particular, they noted that individual researchers have played an important role in ensuring segregation is now recognised as an issue that requires proactive, early-stage measures (Interview 3, 2022). Here, close relations and collaboration between university researchers and the City of Helsinki was mentioned as an important strength, as was the fact that the authorities have funded university research to help gain a better understanding of the city’s development. Alongside this, the City of Helsinki’s own research and statistics unit has proven to be an important resource, helping establish the principle that data and research-based evidence are important prerequisites for good governance.
A key challenge faced by the City of Helsinki is that it is a large and complex organisation, within which there are numerous producers and users of data. Interviewees described how the data and knowledge used by the City of Helsinki constitutes a complex web, with different organisational actors and branches working towards common strategic goals (Interview 3, 2022). However, there is not always a clear overview of what types of data and indicators actually exist. Another issue is that the system currently in place does not necessarily allow data to be shared between different branches of the administration. As such, mechanisms to aid the internal flow of information are needed.
A situation in which data becomes more widely available and used for different purposes throws up its own issues, however. One concerns how data and indicators are interpreted. For instance, when dealing with segregation, there is a risk that oversimplified conclusions are made, or that cause and effect are mixed up (Interview 3, 2022). Interviewees expressed concerns that politicians and policy-makers may have an exaggerated belief in the power of data to provide solutions to problems. In this regard, they underlined that a strong understanding of and ability to interpret data and indicators is needed to make well-informed decisions.
Another issue concerning monitoring of segregation or urban renewal-related interventions is that change often occurs relatively slowly, which makes frequent monitoring difficult. In some cases, the City of Helsinki conducts monitoring on a quarterly basis, which may be too frequent to identify noticeable changes in long-term trends (Interview 3, 2022). On the other hand, various resident surveys are being used to collect short-term indicators, which enables residents to make their voices heard. This is particularly important for urban regeneration projects where large infill construction is planned in a certain area. These more short-term indicators can be collected as necessary, and are often extremely useful in understanding the different effects of measures carried out locally.
4.1.5 Key takeaways
Finland’s increasing emphasis on data, indicators and research-based knowledge in support of policy-making and planning has taken place in parallel with growing political, public and scholarly interest in segregation and social inclusion. While there are currently no national indicators for monitoring segregation in Finland’s cities, steps are being taken to develop harmonised urban segregation indicators. At present, however, the exact role these indictors will play remains unclear.
The role of indicators is more established in some of the larger Finnish municipalities, with the City of Helsinki the clearest example of this. Here, counteracting segregation is treated as a clear strategic focus, and the city authorities have a long history of using data and indicators to support policy and planning interventions. Various quantitative and qualitative indicators are used to monitor progress towards the city strategy and the SDGs. Indicators are also used to determine which geographic areas should be targeted by area-based regeneration interventions, as well as which schools should be given needs-based funding in order to counteract school segregation. In addition, surveys used to monitor perceptions of security and wellbeing are important aids for policy and planning interventions, particularly when backed up by data on – among other things – the housing stock, built environment, and socio-economic and demographic characteristics of different neighbourhoods.
In Helsinki, research has played a central role in putting issues of segregation and social inclusion on the policy agenda. One of the challenged faced, however, is that the City of Helsinki is a large and complex organisation with numerous producers and users of data. Moreover, data cannot always be shared easily between the different branches of the administration. In the context of using data to support policy-making, especially when addressing and monitoring segregation, acknowledging the complexities involved in interpreting data and indicators is crucial.
Overall, the general trend seen in the City of Helsinki is that data and research are increasingly being relied on to support strategic decision-making and planning. This necessitates close consideration of not only the benefits and added value this offers, but the potential risks attached to using data and indicators for these purposes.
4.2 Denmark
As discussed in section 3.2, the 2018 Danish national strategy against parallel societies, colloquially known as the ‘Ghetto Strategy’ (Danish Government, 2018), is the fulcrum of the Danish approach to combating segregation. The strategy is strongly based on national indicators, which are used to identify areas experiencing various degrees of vulnerability, based on the levels of income, education, employment, crime convictions and concentration of non-Western immigrants.
Understanding Denmark’s ‘Ghetto Strategy’ – which is highly contested due to its alleged role in stigmatisation, displacement and loss of public housing units (Alves, 2019) – requires retracing the country’s past 30 years of policy development, which has not only seen increased focus on the concentration of ethnic minorities in certain areas, but set social mixing as a desired goal (Fallov & Birk, 2022). By the early 1990s, the topic of segregation had moved to the centre of political debates.
Since then, and especially from 2004, the main policy focus regarding segregation has come to rest on immigrants, legitimising the rhetoric around ‘ghettos’. When a new Conservative government came to power in 2004, it published a strategy explicitly arguing against ghettoisation. At the time, the ‘Danish ghetto’ was not yet considered to exist – rather, it was a process that could still be prevented.
Initially, ‘ghettoisation’ was primarily referred to in Danish policies and political debates as being the result of failed urban planning, integration and employment policies. By 2018, however, the term was mainly being used to describe the implications of high immigration. Back in 1994, a ministerial report described the idea of the ‘ghetto’ as a ‘misleading concept’ (Stjernberg, Oliveira e Costa, et al., 2020), and the term was eventually replaced – at least officially – by ‘parallel societies’ in the 2018 national strategy (Danish Government, 2018).
Although it was a Conservative government that instated the Ghetto Strategy, the Social Democratic governments that followed in 2019 and 2022 retained most of its initiatives and policies, which are now part of the country’s national strategy against parallel societies. Furthermore, in 2021, the Danish Ministry of Immigration and Integration introduced a new statistical category for migrants called MENAPT, which singles out people from North Africa and the Middle East. This category has since been used in statistical analyses of high crime and low employment rates (European Commission, 2020).
4.2.1 Denmark’s approach to combating ‘parallel societies’
Denmark’s national segregation indicators are strongly linked to the ‘ghetto’ and ‘parallel society’ strategies described previously. ‘Ghetto lists’ – government-curated lists of areas defined as ‘ghettos’ (or, from 2018, ‘parallel societies’) (Ministry of the Interior and Housing, 2022) – have been published by the Ministry of the Interior and Housing (currently Ministry of Social Affairs and Housing) every year since 2010. Between 2010 and 2018, these segregation indicators went from being simply a monitoring tool without concrete policy consequences, to becoming a central element not only in determining funding allocations for social welfare initiatives, but for drastic physical transformations of specific areas (Interview 2, 2023).
As of 2022, four categories of residential areas feature in the national strategy against parallel societies: 1) ‘vulnerable housing areas’; 2) ‘parallel societies’; 3) ‘transformation areas’; and 4) ‘prevention areas’. These are distinguished according to indicators concerning employment, income and education levels, crime rate, and presence of immigrants and descendants from non-Western countries (see Box 3 below).
Box 3. Categorisation of vulnerable areas in the Danish national strategy against parallel societies
- A vulnerable residential area is defined as a public housing area of at least 1,000 residents that meets two or more of the following criteria:
- More than 40% of residents aged 18–64 are outside the labour market or educational system (calculated as an average over the past two years).
- The proportion of residents convicted of violating the Penal Code, the Gun Law or the Act on Euphoriant Substances is at least three times the national average (calculated as an average over the past two years).
- More than 60% of residents aged 30–59 only have a basic education.
- Residents aged 15–64 (excluding students in further education) earn an average gross income that is less than 55% of the average gross income of the age group in the region as a whole.
- A parallel society is a vulnerable residential area where the proportion of immigrants and descendants from non-Western countries exceeds 50%.
- A transformation area is an area that has been listed as a ‘parallel society’ for four consecutive years.
- A prevention area is an area ‘at risk’ of becoming a ‘vulnerable residential area’.
Source: Danish Government, 2018
Besides the so-called ‘ghetto lists’, which are the main source for identifying areas experiencing social vulnerability, the national Integration Barometer is a statistical tool covering the following thematic areas: labour, education, Danish language skills, citizenship, equal treatment, support and vulnerable areas (National Integration Barometer, 2023). Specific indicators include the number of parallel societies, as well as the numbers of vulnerable, transformation and prevention areas, both for the country as a whole and for all Danish municipalities. It should be noted that these indicators only encompass immigrants and descendants of immigrants with non-Western origin. The barometer includes data for different years, and can thus be used for examining changes over time (for some indicators since 2012).
In addition, knowledge about the development of areas targeted by relevant policy interventions, including the effects of initiatives linked to the national strategy against parallel societies, is being continuously produced by researchers from Aalborg University and the Danish Center for Social Science Research (VIVE). This research receives funding from the National Building Fund and is published on a dedicated website named Udsatte områder (Udsatte områder, n.d.).
Figure 9. Map showing the location of vulnerable areas (green), parallel societies (yellow) and transformation areas (red)
Source: Adapted from Udsatte områder, n.d.-b
When examining changes over time using the Integration Barometer data, it can be observed that the number of vulnerable areas, parallel societies and transformation areas all decreased between 2018 and 2023, respectively from 43 to 19, from 29 to 12, and from 15 to 8 (see National Integration Barometer, 2023). These results, while showing that the national policy has been effective in terms of the goals set (reducing the concentration of immigrants, low-income or unemployed people, and people with criminal convictions), this has been achieved in part by reducing public housing units and displacing vulnerable communities (Interview 1, 2023).
More specifically, where the national list indicates an area has been a parallel society for more than four years, the strategy stipulates a physical transformation process must be initiated, including reducing social housing in that area to 40% or less than current numbers. Consequently, local municipalities and social housing associations have to either tear down social housing units or sell them as owner-occupied or private rental properties. Here, it is relevant to note that while the criteria for determining which areas are included on the ‘ghetto lists’ and then subject to physical transformations are set nationally, municipalities have their own statistical offices to monitor the progress of particular areas and customise local interventions in close collaboration with housing associations (Interview 2, 2023).
A number of initiatives have also been put in place to prevent areas becoming parallel societies in the first place, and thus avoid having to undergo physical transformation processes, which can have substantial social impacts. These initiatives encompass social policies aimed at – among other things – improving the employment levels, Danish language skills, education and professionalisation of young residents, as well as criteria to allocate new or existing public housing. Where areas are at risk of becoming vulnerable (prevention areas), the allocation criteria for public housing units are set based on the socio-economic profile of households via collaboration between municipalities and housing associations. For example, employed people without crime convictions may be prioritised for public housing units (Interview 2, 2023).
The Ghetto Strategy exemplifies a common tendency seen in international urban development since the 1990s, whereby concentrated social vulnerability is addressed by mixing public and rental housing with market-rate housing and other forms of ownership (Bridge et al., 2011). The underlying idea is that a mixed supply of housing attracts a more mixed composition of residents, including people with greater economic and social resources, which in turn alleviates an area’s social problems. Nevertheless, the question remains: how should urban development be arranged and designed so that these mixed districts become well-functioning, socially sustainable local communities?
4.2.2 Vollsmose, Odense: A ‘transformation area’
As of December 2022, the residential area of Vollsmose in Odense – Denmark’s third most populous city – was the largest area on the list of ‘parallel societies’, having been categorised as a ‘transformation area’ (Ministry of the Interior and Housing, 2022). Vollsmose has been on the list since 2010 and, despite some improvements (Bech-Danielsen et al., 2020), the area still meets all the transformation area criteria. There are approximately 3,100 dwellings in Vollsmose, of which 2,900 are social housing units for families, with the remainder privately owned rental housing (City of Odense, 2023).
Figure 10. Vollsmose in Odense, undergoing large-scale redevelopment
Source: Fremtidens Vollsmose
A number of initiatives linked to Vollsmose being designated a transformation area have been implemented since 2017, encompassing both physical transformation and social policy measures. A comprehensive realisation plan published in 2021 (City of Odense, 2021a) set out the strategic vision for developing a ‘future’ Vollsmose by 2030 (City of Odense, 2021b). The plan is organised around eight sub-programmes focused on: 1) area attractiveness; 2) economic growth, jobs and education; 3) safety; 4) professional growth for children and young people; 5) children’s wellbeing; 6) culture; 7) public health; and 8) mixed urban and residential areas.
In addition, a statutory development plan (Civica et al., 2019b) for Vollsmose was launched in 2019, based on a collaboration between three political parties, the municipality of Odense, and the housing associations Civica and FAB (City of Odense et al., 2019b). The plan aims – reflecting the national legislation for ghetto areas – to reduce social family housing to a maximum of 40% of the total stock by 2030. Among the main measures put in place to achieve this are:
- Demolition of approximately 1,000 social housing units;
- Renovation of remaining social housing units;
- Construction of 1,600 private dwellings;
- Construction of non-residential buildings for private or public purposes in order to enhance Vollsmose’s attractiveness; and
- Construction of new infrastructure to improve connections within Vollsmose and better connect the area to central Odense, thereby improving the physical characteristics of an area currently surrounded by wide, busy roads.
The housing interventions in Vollsmose are designed to alleviate the poverty and social issues linked to the area’s high concentration of public housing. Regarding the demolition and reconstruction of public housing, the agreement between the City of Odense, Civica and FAB requires that a number of relevant issues be considered (Civica et al., 2019a).
First, new social housing must be located in mixed districts representative of different generations, forms of ownership and socio-economic backgrounds. Second, the city council’s political parties have an agreement that the construction of social housing must be undertaken in conjunction with private investment in order to create synergy and promote general urban development. Third, as specified in the area’s relocation plan (Civica et al., 2019a), of the total 25 million Danish kroner allocated for reconstruction interventions, 15 million is already earmarked, such that each housing unit demolished in Vollsmose is to be replaced according to a 1:1 principle (City of Odense et al., 2019a). Concretely, this means that for each social family housing unit in Vollsmose that is to be demolished, the relevant housing association will be offered a capital contribution towards a replacement social housing unit (not necessarily to be built in Vollsmose). Thus, the transformation becomes a mutual responsibility, with housing associations taking on the construction of replacement buildings and rehousing residents, the municipality funding the 1:1 capital subsidy that makes this possible.
This collaboration between the municipality and housing associations is important not only in terms of the physical transformation process, but for setting up pre-emptive initiatives to counteract segregation. Here, there is also a strong focus on social policies, employment and education as possible means to achieve a welfare boost.
For instance, the Social Housing Masterplan (Social Housing Vollsmose, 2021), which is supported by the National Building Fund (Landsbyggefonden), is built around the following four areas of interest: 1) education and life chances; 2) employment; 3) crime prevention; and 4) cohesion and citizenship. Within this framework, local associations work to promote participation and engagement among Vollsmose residents, thereby improving safety and cohesion, and cultivating a sense of belonging.
BoligSocialt Hus is one such collaborative initiative, bringing together a housing organisation, resident representative and the municipality to strengthen social cohesion in Odense’s vulnerable residential areas (BoligSocialt Hus, 2024). Box 4, which looks at planning interventions in Copenhagen, provides a broader perspective on how indicators are used locally in Danish municipalities to help create more socially inclusive, mixed neighbourhoods.
Box 4. Indicators supporting planning interventions in Copenhagen
Social inclusion as it pertains to Danish national and local initiatives is, generally speaking, primarily linked to combating segregation, with municipalities sometimes creating their own, context-specific, indicators. Here, the City of Copenhagen represents a relevant case study when it comes to categorising ‘prevention areas’ – that is, areas at risk of becoming vulnerable and, potentially, parallel societies.
Using detailed socio-economic data, the municipality identifies red, yellow and green prevention areas, assigning strict criteria to each of these for renting out public housing (City of Copenhagen, 2021b). The tool for determining the rental criteria is called ‘flexible renting’ (fleksibel udlejning), and is set according to an area’s specific socio-economic characteristics (City of Copenhagen, 2021b).
Another relevant example in terms of promoting better social mixing and inclusion using national indicators is Christiania in Copenhagen. In August 2022, Christiania – known as a hippie enclave and one of the city’s main touristic attractions – entered into an agreement with the Ministry of the Interior and Housing and with the Housing and Planning Authority regarding the establishment of 15,000 m2 of public housing by 2031. The aim of the agreement, which is part of the Fund for Mixed Cities (see section 3.2), is to create social mixing not only in vulnerable areas, but in areas (particularly in large cities) where it would be difficult or impossible for people with lower incomes to reside on a free-market basis.
4.2.3 Key takeaways
In the Danish context, a vast array of detailed socio-economic data is used to inform national- and local-level indicators of segregation, which can then be applied to relevant policy. To date, the results have been mixed and sometimes contested. While ‘ghetto lists’, as well as the legislation informing pre-emptive and transformation measures, are national, local actors – particularly municipalities and housing associations – are centrally involved in using indicators to set up area-based initiatives. This is exemplified by the case of Vollsmose, Odense, examined in this section.
The main indicators affecting Denmark’s segregation-related policies and physical interventions are those informing the so-called ‘ghetto lists’ of areas considered vulnerable or at risk of becoming vulnerable based on levels of income, education, employment, criminal convictions and concentration of non-Western immigrants. The role of the indicators is threefold.
First, they act as a monitoring tool for checking on vulnerable areas year by year. Second, they are a pre-emptive tool for preventing areas at risk becoming vulnerable. Here, indicators inform the selection criteria for renting out social housing units, thereby preventing a further concentration of vulnerable groups (see the case of Copenhagen in Box 4). Third, they inform policies for the physical transformation of areas where a high proportion of social housing and vulnerable groups have contributed to poor living conditions and strong segregation (see Vollsmose). At the same time, the indicators inform local level social welfare initiatives focusing on, for instance, education, language and labour market training.
Several challenges arise from the use of indicators to classify vulnerable areas and parallel societies, as well as defining the initiatives to be implemented in response. The first concerns the public availability of vulnerable area and parallel society lists, which risks further stigmatising the areas involved. The second is the connection between indicators and transformative interventions, which, in order to adhere to the nationally set limit of no more than 40% social housing in vulnerable areas, have led to several public housing units being demolished, households being displaced, and the promise of 1:1 replacements not always being fulfilled. Finally, quantitative indicators do not give any qualitative information on what it’s like is to live in areas defined as vulnerable, including what kind of communities are established or what sense of belonging exists among residents. Moreover, indicators cannot capture individual experiences, such as how someone might feel about being relocated because their housing unit has been demolished. As such, policy-makers should consider making greater use of qualitative data in order to ensure the indicators they use are both more comprehensive and nuanced.
On the other hand, the use of indicators as monitoring tools in Denmark has emerged as a potentially useful way of counteracting segregation. In this vein, it should be highlighted that the use of indicators to inform Denmark’s social mixing policies is not purely limited to vulnerable areas – increased efforts are also being made to ensure affluent areas become more mixed. This is reflected in the previously mentioned case of Christiania, as well as in the use of the Fund for Mixed Cities to acquire land in more expensive areas on which housing associations can build public housing.
4.3 Norway
In Norway, the drive to strengthen social inclusion arises from a recognition of the potential impacts of a neighbourhood’s characteristics (e.g. its environment, location, accessibility aspects and social environment) on residents’ life opportunities. At the national level, a number of relevant strategies have been introduced in recent years (see section 3.3). Furthermore, the SDGSs have prompted greater awareness of the connections between the quality of local environments, social cohesion, social mobility and public health. In order to better understand these connections, increasing political attention is being directed at developing indicators that describe social conditions in different urban areas and so be used to inform policy development and implementation.
Several of Norway’s key policies mention the need for reliable indicators to support decision-making and assess policy efficacy. For instance, the 2019‒2022 Integration Strategy refers to the government’s intention to ‘further develop the performance indicators in the area of integration, to ensure a good basis for measuring the effect of policies’ (Ministry of Education and Research, 2019, p. 65). Similarly, the 2019–2023 National Expectations Regarding and Municipal Planning states that the government will ‘continue work on developing indicators for all the sustainability goals’, which ‘must be adapted to regional and local conditions, so that counties and municipalities that wish to do so, can measure the effect of their own efforts’ (Ministry of Local Government and Regional Development, 2019, p. 6).
Regarding segregation more specifically, the official report ‘Living Conditions in Cities – Good Communities for All’ calls for more systematic knowledge (Ministry of Education and Research, 2020). While many municipalities have developed their own indicators for monitoring welfare conditions, the routines, content and use of these indicators vary. Given this, the documents mentioned above indicate that the central government will increasingly take a coordinating role in further developing relevant indicators. At the same time, the documents emphasise the role of municipalities as the main end users of such data. Overall, the main rationale underlying the improvement of social indicators is strengthening municipal decision-making and local-level integration efforts.
4.3.1 Policies and strategies
Currently, no national-level indicators are actively being used to monitor segregation in Norwegian cities. Instead, many municipalities – including all the big cities – have developed their own systems for monitoring local variations in welfare conditions. How, and to what degree, these systems are used varies. In most cases, however, the municipalities draw on socio-economic indicators from Statistics Norway (SSB), combined with other analytical data, for instance from the Norwegian Institute of Public Health, and/or Ungdata, a national data collection scheme targeting youth and children in Norwegian municipalities through surveys (Ungdata, n.d.).
‘Living Conditions in Cities’ suggests developing a harmonised system for monitoring segregation across Norway’s municipalities, in order to produce comparative knowledge (Ministry of Education and Research, 2020). According to the report, a national indicator system would provide a number of benefits, including helping to:
- target public authority efforts at areas with the greatest need, and equitably distribute funds across different areas;
- enhance understanding of areas vulnerable to risks, enabling the implementation of preventive measures;
- facilitate prioritisation of resource allocation across sectors (e.g. education, healthcare, recreation, housing);
- assess the needs of area-based initiatives;
- streamline municipalities’ compliance with their Public Health Act responsibilities, thereby ensuring they maintain a comprehensive understanding of the local environmental factors impacting public health; and
- create a unified analysis framework that reduces the financial and operational barriers faced by municipalities, enabling easier comparison across regions.
In addition, the report mentions the Swedish Segregation Barometer (discussed in section 4.4) as a potential source of inspiration, and suggests municipalities could receive support in analysing and making use of information – for instance, from Statistics Norway – in order to avoid indicators being misinterpreted. To concretise the work of developing an indicator system, a follow-up report was delivered to the Ministry of Local Government and Regional Development (KDD) in 2022 (Ministry of Local Government and Regional Development, 2022).
4.3.2 Qualitative and quantitative indicators in area-based policies
Over recent decades, area-based policies have become a key approach in Norway for improving neighbourhood conditions and addressing inequalities in targeted areas. Furthermore, these projects have provided an important arena for public innovation and new ways of collaborating across levels and departments. Various socio-economic indicators on living conditions (e.g. unemployment, educational attainment, income, neighbourhood resident turnover, and living space per person) are used to identify which areas should be targeted by area-based investments.
Moreover, the indicators provide insights on the broader issues affecting an area, which can result in reduced attractiveness and thus lower housing prices, leading to a greater concentration of groups with a lower ability to pay for housing. Thus, statistics on living conditions are also used as an early indicator for challenges posed by the physical environment (Lund, 2014). Given the complex, mixed challenges often faced in targeted neighbourhoods, statistical indicators are usually supplemented by local knowledge and different mapping methods.
How best to make investments and initiatives measurable has been a recurring topic, with various assessment tools tested in this respect. For instance, the State Housing Bank (Husbanken) developed an interactive tool in 2017 visualising different indicators for the 14 areas included in the ‘Area Boost’ (Områdeløft) project (nine areas in Oslo, three in Bergen, one in Drammen, and one in Trondheim) (Husbanken, 2023). The active use of this platform was limited, however, as longitudinal data was scarce and the area unit sizes involved were too large to identify specific neighbourhood challenges. The analytic utility of some indicators was also questioned – for example, the perceived safety measurement included both petty crime and serious offences, including acts of violence. These shortcomings point to wider methodological issues when it comes to quantitative indicators, such as access to longitudinal data, defining relevant unit sizes for measurements, and determining how different aspects should be monitored (Interview 10, 2022; Interview 11, 2022).
Reliance on misleading data from indicators is a potential risk when working with area-based initiatives (Interview 9, 2022). While indicators can help locate areas for funding, it is unlikely these indicators will change within the timeframe of a project, as reversing segregation is a slow process that requires structural change beyond the means of area-based investments.
In other words, indicators have limited applicability in evaluating efforts. Even if an indicator improves, it is difficult to assess whether this is due to a particular initiative or the outcome of other welfare policies, societal forces and/or house market fluctuations. Similarly, it is hard to determine what would happen if no initiatives were set in motion. Even so, the direct benefits of initiatives are often of significant value to residents in terms of increased neighbourhood satisfaction and cultivating a sense of ownership and belonging, which can be documented using qualitative methods, such as interviews and surveys.
4.3.3 The role of indicators in Oslo
Oslo has long been characterised by a socio-economic divide between the more affluent groups living in the city’s western parts, and the lower-income groups living in the eastern parts (OsloMet, 2023; Wessel, 2000). To compensate for neighbourhood differences, several area-based regeneration initiatives involving collaboration between the state and the municipality have been implemented. This section addresses the use of indicators in these efforts and in the city’s neighbourhood policy (Områdepolitikk), which was instated following the first major area investment project in the Groruddalen area.
Area-based initiatives
More than a fifth of Oslo’s population resides in the north-eastern district of Groruddalen, characterised by large housing estates built during the post-war decades. A ten-year collaborative project (Områdesatsing) between the state and the city was initiated in 2007 with the aim of improving the quality of Groruddalen’s neighbourhoods. Prior to this initiative, similar efforts had been carried out on a smaller scale in Oslo’s eastern city-centre districts, including Miljøbyen Gamle Oslo (Unstad & Whist, 1997) and Handlingsprogram Oslo indre øst (Holm & Søholt, 2005).
Figure 11. Haugenstua, located within the Groruddalen district in Oslo
Source: CCO 1.0
In 2017, the Groruddalen project was extended for another term (2017–2026), alongside new projects established in Oslo’s south-eastern suburban areas (Oslo sør-satsingen 2018–2026) and the inner east (Oslo indre øst-satsingen 2019–2026) (City of Oslo, n.d.-b, n.d.-a). While physical interventions were prioritised during the first project period, the second period placed greater emphasis on the overlapping dimensions of physical and social challenges. Specifically, the main goal of the current investment projects in Groruddalen is to contribute to lasting service and neighbourhood quality improvements in areas of greatest need, thereby helping residents become financially independent and actively included in their local and wider communities (City of Oslo, 2016).
The funding and organisation of investments is divided into three strategic sub-programmes focused on: 1) employment; 2) childhood and education; and 3) local environment. Each area within the targeted subdistricts receives funding for improving local area conditions (‘områdeløft’). Given the overarching aim of bringing about long-term change, it has been difficult to make concrete assessments of the projects’ results and effects. As such, many of the evaluations have focused on the frameworks, organisational structures, work methodology and processes developed to ensure the efforts achieve long-term results (Pwc & Fafo, 2021). Here, a common goal has been to provide information that can be used for learning, management and developing ways of assessing both smaller and larger projects. At the same time, it is important that measurements reflect desirable and realistic effects, and that the overall benefits of the indicators are greater than their cost (City of Oslo, 2022).
There have been variations in the process of selecting areas for funding. Initially, when the state and the City of Oslo allocated funds for initiatives in Groruddalen, the area’s prevailing challenges were so widely acknowledged that no fresh analyses were deemed necessary (Interview 9, 2022). When it came to pinpointing specific subdistricts for funding, however, it became evident that the gathering of additional information was imperative. This necessitated delving into data on a more granular geographical scale, as well as reassessing the geographical boundaries of statistical units in order to accurately capture the divergent characteristics of neighbourhoods (Interview 9, 2022). For instance, certain subdistricts contain high- and low-income populations residing in close proximity but in distinct neighbourhoods. Consequently, relying solely on statistical averages could obscure significant discrepancies between streets and blocks (see also Lund, 2014).
While socio-economic statistics have been prioritised as foundational in selecting areas for funding, the overarching goal is to address the multifaceted challenges faced by communities. Beyond socio-economic factors, neighbourhoods often grapple with issues such as poorly maintained public spaces, heavy traffic congestion, environmental pollution and inadequate community amenities (Lund, 2014).
Uncovering these challenges has required various mapping techniques and participatory methods. Furthermore, insights gleaned from surveys conducted by the city have been instrumental in gaining a better understanding of residents’ perceptions and evaluations of their districts. Here, it should be stressed that local knowledge extends beyond problem identification, serving as a crucial asset in devising solutions, guiding interventions and bolstering community resilience.
The funding allocated to an identified neighbourhood typically encompasses its surrounding areas in order to foster community engagement and leverage local resources from a broader catchment area. A multiscale approach has therefore been advocated to monitor initiatives at the neighbourhood, sub-district and district levels, which – along with lessons learned from initiatives in Groruddalen – has been integrated into Oslo’s city-wide neighbourhood policy, initiated in 2017.
Neighbourhood policy
The main goal of the city-wide neighbourhood policy (områdepolitikk) is to: ‘contribute to ensuring that all local areas in Oslo are experienced as good and safe places to live and grow up’ (City of Oslo, 2017). The policy lays out three main strategies, the first of which is establishing a monitoring system that covers all of the city’s local areas. Statistical analysis is considered an important means for the municipality to proactively identify and address negative trends at an early stage. The relevant statistics encompass – among other facets – living conditions, demographics, environmental stressors and housing market dynamics. This systematic approach is intended to furnish Oslo’s city council with a robust foundation for making informed political decisions regarding the strategic allocation of initiatives (City of Oslo, 2017).
Drawing on learnings from Groruddalen, the policy states that statistical information should be combined with other kinds of data when selecting areas (City of Oslo, 2017). While the exact form this other data should take is not specified, residential participation and the knowledge of public servants in the community is highlighted as relevant. Moreover, the policy emphasises that detailed lower-level geographical information should be collected in order to better identify local differences.
A monitoring system, together with standardised approaches for selecting areas for investments, was formalised in 2020 (City of Oslo, 2020). The monitoring system, which collects data for each of the city’s 98 subdistricts, is used by the municipal administration to identify areas that score significantly lower on several socio-economic indicators compared to the city average. In addition, Statistics Norway’s basic statistical unit, which divides the city into 589 geographical areas, provides information at a lower geographical level on employment ratios, education levels, non-Western immigrants, homeownership and moving frequencies.
The monitoring system does not, however, operate as a list of criteria with threshold values – rather, it is used for making initial comparisons of areas. This provides a basis for identifying areas that should be prioritised, while leaving room for other considerations. Currently, the monitoring system tracks nine indicators (see Table 11). Going forward, additional indicators from other statistical registries may be added in, such as changes in housing prices, school statistics and environmental factors.
Table 11. Indictors for monitoring local area development and selecting areas for renewal in Oslo
Theme | Variable | Territorial level |
Employment |
| Sub-district (delbydel) Basic statistical unit (grunnkrets) |
Not completed upper-secondary school |
| Sub-district (delbydel) |
Low educational level |
| Sub-district (delbydel) Basic statistical unit (grunnkrets) |
Low-income families |
| Sub-district (delbydel) |
Non-Western immigrants |
| Sub-district (delbydel) Basic statistical unit (grunnkrets) |
Overcrowding |
| Sub-district (delbydel) |
Housing tenure |
| Sub-district (delbydel) Basic statistical unit (grunnkrets) |
Social security benefits |
| Sub-district (delbydel) |
Migration |
| Sub-district (delbydel) Basic statistical unit (grunnkrets) |
Source: Municipality of Oslo, 2020
Box 5. Additional examples of indicator systems in Norway
- Boligsosial monitor, developed by the Norwegian State Housing Bank (Husbanken), provides an overview of the social housing situation both in Norway overall and in its municipalities. The information gathered about social housing challenges in a particular municipality helps inform local-level analyses and measures. The system does not provide comparative data at a more detailed level than the municipal level.
- Utenfor-regnskapet, maintained by the Norwegian Association of Local and Regional Authorities (KS), aims to demonstrate from the perspective of municipalities how much society can save by pursuing a preventative – rather reactive – approach, and by investing in people rather than seeing them as an expense.
- Bydelsfakta, developed by the City of Oslo, includes various official statistics concerning population, living conditions and housing in Oslo’s administrative districts and subdistricts. While the tool can be used for district- and sub-district-level analysis, it does not include data on more detailed spatial levels, meaning it is not detailed enough to be used in area-based initiatives.
4.3.4 Key takeaways
Norwegian municipalities have access to a variety of demographic, socio-economic and socio-cultural indicators designed to improve social sustainability in cities. While many of these have been developed by national-level actors and agencies, such as Husbanken, KS and Statistics Norway, a number of municipalities have developed their own systems. How – and the extent to which – these indicators are used varies depending on municipal goals and resources.
Although there is no comprehensive national monitoring system for following up on segregation trends, such a system is now on the government agenda following the recommendations of a Norwegian Official Report on ‘Living Conditions in Cities’ (NOU 2020:16) (Ministry of Education, 2018). A harmonised national system would give a comprehensive overview of all regions, providing comparative data with which to assess policies and efforts at different levels. More specifically, such a system could not only support the process of selecting areas for state–municipal investments, but help municipalities perform regular tasks, such as distributing welfare funds between administrative districts.
Area-based initiatives have gained popularity as a method for offsetting neighbourhood disadvantages and strengthening local communities. Such projects utilise both quantitative and qualitative indicators to establish a holistic understanding of local challenges. Statistical data is used in the early stages to identify areas that have significantly lower scores compared to the city average according to several socio-economic indicators. Other analyses are also taken into consideration when weighing up the social and physical challenges faced by potentially targeted areas. Continuous participation and community involvement is emphasised at all stages of projects in order to ensure funding is tailored to local needs.
An important lesson arising from the experiences of area-based initiatives – as well as from policy work more broadly – is that granular-level knowledge is required to determine which challenges are characteristic of a local area. The geographical borders of statistical units also matter, as standard units may not correspond with actual neighbourhoods, obscuring the differences that play out in local communities. In addition, access to data on multiple scales can further assist in a range of efforts and policies directed at the neighbourhood, sub-district and district levels.
The biggest risks posed by indicators relate to misinterpretation or wrongful application. Regarding area-based interventions specifically, quantitative indicators can be useful in detecting areas with complex challenges. If the ambition is to use indicators to follow up on an intervention’s effects, however, it should be acknowledged that specific indicators are unlikely to reveal noticeable changes within programme periods, which typically have a limited, relatively short, duration. Thus, while indicators may be useful tools for monitoring changes in social structures and segregation patterns over longer periods of time, they should be treated with caution when determining the impacts of time-limited projects.
A recognised dilemma arises when area-based investments are justified by existing disparities in welfare conditions, yet their primary objective is not necessarily to resolve these disparities. Hence, it is crucial that the selection of indicators aligns with realistic goals and ambitions. As emphasised earlier, although indicators can significantly bolster policies aimed at mitigating segregation, there are inherent risks and challenges involved. It is therefore imperative that the benefits derived from these indicators outweigh their associated costs.
In sum, local initiatives, neighbourhood enhancements and public innovations necessitate a distinct set of evaluation tools, wherein indicators play a pivotal role in facilitating policy development and implementation.
4.4 Sweden
Various initiatives have been launched in recent years aimed at monitoring, understanding and addressing segregation trends across Sweden. In this context, the Segregation Barometer stands out as a key tool for visualising, analysing and tracking segregation dynamics at different territorial scales. As such, the tool has been widely used to support policy and planning interventions at the national, regional and municipal levels, and for targeting interventions in local communities and neighbourhoods.
Besides examining the Segregation Barometer, this chapter addresses how data and indicators are used in both Örebro County and Örebro Municipality to address segregation challenges and support policy and planning interventions. Within Örebro County, various data related to socio-economic and health status has been used to categorise areas. Örebro Municipality, meanwhile, has utilised the Segregation Barometer to assess the efficacy of local initiatives, including master plans aimed at fostering mixed communities and reducing segregation.
4.4.1 The Segregation Barometer
The Segregation Barometer (Segregationsbarometern) is an interactive web-based monitoring tool for visualising, analysing and following up on segregation trends in Sweden. Development of the tool was led by the Delegation Against Segregation (Delmos). In 2019, as part of its efforts to better understand segregation, the government tasked Delmos and Statistics Sweden (SCB) with mapping what segregation patterns look like in Sweden, and how they have evolved over time (Ministry of Employment, 2020). The Segregation Barometer, launched in 2021, is a concrete output from this work.
Although development of the tool was led by Delmos, several other agencies and actors with relevant expertise were consulted during the process (Interview 13, 2023). Delmos was discontinued at the end of 2022, following which the Swedish National Board of Housing, Building and Planning (Boverket) assumed responsibility of administering the Segregation Barometer (Boverket, 2023b).
The Segregation Barometer is freely available for all users, but is primarily intended for practitioners and decision-makers working in municipalities, county councils, national authorities or other organisations dealing with segregation. The overall aim of the tool is to support segregation-related policy and planning through provision of an enhanced knowledge base, and the highlighting of questions and needs that require specific attention (Boverket, 2023b). Towards this end, the tool sets out segregation patterns at different geographic levels based on common measures.
Dimensions, indicators and territorial scales
The Segregation Barometer includes various indicators relevant to understanding socio-economic residential segregation patterns and development trends over time, which can be visualised in the form of maps, diagrams and tables. An interviewee for this study cited the US Opportunity Atlas tool as a source of inspiration for the Segregation Barometer (Interview 9, 2022).
The data in the Segregation Barometer originates from Statistics Sweden’s statistical registers, while the indicators included are based on six key priority areas: 1) socio-economy; 2) housing and public services; 3) labour market; 4) education; 5) democracy; and 6) civil society and health (see Table 12). These priority areas are based on the core themes set out in the Swedish government’s 2018 long-term strategy to reduce and counteract segregation (see section 3.4), although in some cases they are termed differently.
The number of indicators varies between thematic areas, as not all statistics are available at the more detailed territorial levels. The indicators can be broken down according to different background variables, such as gender, age group, foreign-born or Swedish-born, and for some indicators educational level and income quintile. The tool includes time series data, which allows examining change over time. For some indicators, data extends back to 2011 (Boverket, 2022c).
Table 12. Indicators according to different dimensions of segregation included in the Segregation Barometer (Delmos, 2021a)
Dimensions | Indicators |
Socio-economy |
|
Housing and public services |
|
Labour market |
|
Education |
|
Democracy |
|
Civil society and health |
|
The Segregation Barometer includes national-, regional-, municipal- and sub-municipal-level indicators. At the sub-municipal level, indicators are available at the level of regional statistical (RegSO) areas and demographic statistical (DeSO) areas, which means more localised differences can be detected at the neighbourhood or district level.
Furthermore, the tool is based on the idea that segregation is relational, meaning that conditions in a specific place are also determined by the broader conditions in the city or region it is part of. One of the tool’s purposes is therefore to illustrate how local residential (RegSO or DeSO) areas relate to each other at the municipality and regional level (Boverket, 2023b).
In addition to the individual indicators measuring different aspects of socio-economic segregation, the Segregation Barometer includes an inequality index (ojämlikhetsindex) developed by Delmos and Statistics Sweden (Delmos, 2021b). The index, which is based on disposable household income, describes the degree of segregation within a municipality or region based on the residential patterns of different socio-economic groups. More specifically, it describes how evenly distributed the lowest and highest income groups are (based on quintiles) in different (DeSO) areas in a municipality or region.
The Segregation Barometer also allows for the classification of area types (områdestyper), which in turn enables comparison of different residential districts (RegSO) based on their socio-economic conditions. The classification relies on a weighted socio-economic index constructed using the following three indicators: 1) proportion of people with a low economic standard; 2) proportion of people with a low educational level; and 3) proportion of people who have received financial aid and/or been unemployed for longer than six months (Delmos, 2021a). In total, there are five area types: 1) areas with great socio-economic challenges; 2) areas with socio-economic challenges; 3) socio-economically mixed areas; 4) areas with good socio-economic conditions; and 5) areas with very good socio-economic conditions.
The area type classifications were developed to complement the inequality index: while the latter shows the degree of segregation, as well as how different income groups are spread out across a municipality or region, the former describes the socio-economic conditions of different residential areas. In this respect, there is a clear connection between the different area types and the degree of segregation shown by the inequality index (Boverket, 2022c; Delmos, 2021a).
Strengths and limitations of the Segregation Barometer
One of the Segregation Barometer’s main strengths is that it builds on a comprehensive dataset harmonised to facilitate analysis of segregation patterns and trends across Sweden at various territorial scales (Interview 13, 2023). Additionally, its open accessibility promotes widespread utilisation for policy formulation and planning purposes, while the uniform territorial classifications further enhances its value by ensuring greater comparability in analyses and improving the coherence of temporal segregation assessments. Challenges arise with the DeSO areas, and given that as a geographical designation they have been created and delimited to be as homogenous as possible, this somewhat impacts the tool’s accuracy in reflecting socio-economic realities (Interview 13, 2023).
Given that municipalities are identified as key users of the Segregation Barometer, it is crucial that the tool is aligned with local needs regarding parameters, data, indicators and area classifications (Interview 13, 2023). Boverket acknowledges that the Segregation Barometer has certain limitations, emphasising its suitability for monitoring segregation rather than providing a comprehensive analysis. In recognition of the complexity inherent to segregation, Boverket advocates supplementing the tool with local perspectives and additional data sources in order to gain a more holistic understanding (Boverket, 2022c).
While the Segregation Barometer predominantly focuses on socio-economic segregation, some of the authorities and segregation experts consulted during the tool’s development phase suggested it would have been useful to also include ethnic segregation indicators (Interview 13, 2023). This is based on the notion that socio-economic and ethnic segregation are closely connected, meaning the tool would be able to provide a more comprehensive picture of residential segregation if both aspects were included.
According to a study interviewee, the reluctance to include indicators such as country of origin may be due to ethnicity having long been a politically sensitive issue in Sweden – more so than in Denmark, for instance (Interview 13, 2023). Nevertheless, several authorities that use the Segregation Barometer have access to a wider range of statistics that can be used to complement the tool’s indicators.
Another widely used tool is the Swedish Police’s nationwide list of vulnerable areas (see Box 6). While the primary purpose of the list is to help prioritise resources within the police, it is also utilised more broadly by various actors to support urban planning and development initiatives in disadvantaged neighbourhoods (Salonen, 2023). According to Delmos (2022), however, the area type categorisation used in the Segregation Barometer allows for more nuanced, in-depth mapping and analysis of socio-economic segregation, based on the notion that segregation is a complex phenomenon. As such, the Segregation Barometer is better suited to supporting spatial planning and analysis than the police list, which was designed to aid the implementation of measures related to combating crime (Delmos, 2022).
Box 6. Police list of vulnerable areas
Since 2015, the Swedish Police has maintained a list of ‘vulnerable areas’ (utsatta områden), defined as places of low socio-economic status where criminals have an impact on the local community. This work – which is carried out collaboratively by local police districts, municipalities and the police’s national operation department (NOA) – is part of a government assignment requiring the police to produce national situation reports (every second year) of disadvantaged areas vulnerable to crime (Polisen, 2023).
The area categorisations build on a national assessment supported by local area descriptions, together with a living conditions index developed by the Swedish Police Authority, Malmö University and Lund University (Delmos, 2022). The index relies on indicators describing economic marginalisation (employment rate, income, educational level); segregation (foreign background); and vulnerable family and housing conditions (overcrowding, single persons with children, number of children aged 0–15, number of young people aged 16–19) (Salonen, 2023).
The categorisation consists of three area types. Firstly, ‘vulnerable areas’ (utsatta områden), characterized by low socio-economic status, and where criminals have a negative impact on society and public institutions. Secondly, ‘risk areas’ (riskområden), which meet all the criteria of vulnerable areas, and moreover are at risk of becoming ‘especially vulnerable’ if no interventions are put in place. And thirdly, ‘especially vulnerable areas’ (särskild utsatta områden), where there are signs of parallel social structures and extremism, as well as high concentrations of criminals who threaten residents, making it difficult for the police to operate in the area. The total number of areas on the list has remained relatively constant since 2019 (Polisen, 2023), with the 2023 list including 17 ‘vulnerable areas’, 15 ‘risk areas’ and 27 ‘especially vulnerable areas’ (PMY, 2023).
4.4.2 Indicators in supporting policy and planning interventions in Örebro
This section focuses on Örebro County, located in central Sweden, and its largest city, Örebro Municipality. The county has a population of approximately 308,000, of which roughly half (159,348) live in Örebro Municipality (Regionfakta, 2024).
Figure 12. Aerial view of Örebro
Source: CCO 1.0
In 2021, a sophisticated tool aimed at clustering DeSOs based on socio-economic indicators was developed in Örebro Country for the purpose of monitoring the county’s year-on-year development (Raptis, 2021). The initiative was commissioned by the culture and non-profit sector within Örebro County’s regional development unit (Interview 14, 2023), with the outcomes published in 2021 in the form of a report (Raptis, 2021) and interactive maps (Region Örebro County, 2021). The report’s primary objective was to delve into the socio-economic characteristics of each area within the county in order to spotlight their influence on participation in cultural, sports, arts and other social activities.
Both the report and its associated tool have since been integrated into the regional development strategy (RUS), which serves as a blueprint for driving development and enhancing resident’s quality of life (Interview 14, 2023). Not only was the tool designed to be reused in future socio-economic analyses, it was created to benefit all areas of the administration by drawing attention to both common and specific challenges faced by the county’s 12 municipalities (Interview 14, 2023).
The tool aims to capture the county’s socio-economic heterogeneity in greater level than can be achieved at the municipality level, thereby supporting the creation of more specific development strategies and directing funding to particularly challenged areas. On top of this, the tool can highlight similarities between areas where collaboration can be fostered. The analysis is currently employed in RUS follow-ups designed to identify which areas should be the focus of development efforts. Specifically, the data has been used to help map Örebro County’s cultural infrastructure (Raptis, 2021).
The clustering relies on nine socio-economic variables: 1) median income; 2) number of sick days per inhabitant; 3) proportion of people born outside the EU/EFTA; 4) proportion of economically active people; 5) proportion of people with a higher education; 6) proportion people receiving financial aid; 7) proportion of people unemployed; 8) proportion of people aged below 20; and 9) proportion of people aged 65 and over (Raptis, 2021).
The choice of indicators came from an established method produced by Statisticon called the social compass (Den sociala kompassen – SEKOM), which classifies areas into five clusters. Based 0n this, the minimum, maximum and mean values of each variable within a cluster was analysed and compared to the mean values of the county overall. Having done so, the clusters were named according to their salient socio-economic traits (Raptis 2021).
The five socio-economic clusters identified in Örebro County and their key characteristics are as follows:
- Orange cluster – ‘City and peri-urban wellbeing’: High-income areas with a large proportion of people with a post-secondary education, many families, and low proportions of unemployment.
- Green cluster – ‘Rural and urban wellbeing’: Wellbeing areas with high employment rates, above average incomes, low need for financial support, and a below average proportion of people with a post-secondary education.
- Purple cluster – ‘Urban mix’: Diverse areas with a high percentage of the population of working age and a high proportion of people with a post-secondary education, but large differences between areas within the cluster.
- Blue Cluster – ‘Structural Transformation’: Areas with ageing populations, below average proportions of employment, relatively low educational levels, and relatively high financial aid needs.
- Yellow cluster – ‘Socio-economic challenges’: Areas with the greatest socio-economic challenges, including low employment rates, low levels of education, low incomes and high percentages of people aged under 65.
The analysis, implementation of the tool and data updates are handled by analysts at Örebro County’s regional development unit. There has also been discussions concerning collaboration with other analysts at the county administration who have implemented a comparable cluster analysis focused on dental health among children and young people using the same DeSo area classification but relying on different variables (Interview 14, 2023). Two reports were published in 2019 and 2024 mapping the interconnections between dental health and socio-economic conditions in areas across the county (Persson & Sannevik, 2019, 2024).
Socio-economic monitoring is also carried out in Örebro Municipality as part of follow-up on the master plan, which aims to reduce segregation through ensuring mixed housing types in neighbourhoods and enhancing access to services, including leisure and green spaces (Interview 12, 2023; Municipality of Örebro, 2021). The follow-up process, which involves evaluating the need for revisions every four years, makes use of the Segregation Barometer – specifically its inequality index and five neighbourhood types (Municipality of Örebro, 2021). Here, the inequality index is used to describe changes in segregation levels across the municipality overall, while the classification of neighbourhood types is used to monitor how non-mixed areas develop over time (Municipality of Örebro, 2021). The analysis focuses mainly on type 1 (great socio-economic challenges), type 2 (socio-economic challenges) and type 5 (very good socio-economic conditions) areas as representative of the extremes of socio-economic segregation. Given that one of the municipality’s key strategic aims is to create more socially mixed neighbourhoods, any increase in the number of areas belonging to these three area types would indicate that this objective has not been achieved (Interview 12, 2023; Municipality of Örebro, 2021).
4.4.3 Key takeaways
When it comes to addressing segregation, the use of comprehensive data and analysis has been acknowledged as essential by Sweden’s policy-makers and researchers. This has resulted in the deployment of various initiatives to monitor, better understand and combat segregation trends across the country.
Foremost among these is the Segregation Barometer, which was designed to provide a comprehensive understanding of segregation at various geographic levels. Focused on socio-economic residential segregation, the tool incorporates indicators encompassing such key priority areas as socio-economy, housing, labour market, education, democracy, civil society, and health.
At the national level, the Segregation Barometer enables stakeholders to analyse trends and disparities across territorial scales, from the national to sub-municipal level. This nuanced understanding of segregation dynamics can then be used to support relevant policy formulation and planning efforts. The tool is also employed at the municipal level, as exemplified by Örebro Municipality, where the Segregation Barometer has been used to assess the effectiveness of local initiatives, including master plans aimed at fostering mixed communities and reducing segregation.
Despite the Segregation Barometer’s strengths, its use also throws up certain challenges, such as ensuring alignment with local perceptions and the need for supplementary data sources in order to provide a more holistic understanding of segregation. In this regard, there have been discussions about incorporating new indicators or broadening its focus to include related phenomena like energy poverty (Interview 13, 2023). As of 2024, the Segregation Barometer remained in widespread use, with new data incorporated into the tool on a yearly basis. Moreover, there have been initiatives to further develop the tool (Boverket, 2023f), while Boverket has continued to publish annual reports on socio-economic segregation in Sweden, the most recent of which was published in summer 2024 (Boverket, 2024a).
Overall, utilising different types of data and indicators to support policy development remains a high priority in Sweden. This is evidenced by the fact that in 2023 the government tasked several key state agencies with incorporating statistical data that can be broken down geographically, thereby facilitating more effective measures related to integration and exclusion (Government Offices of Sweden, 2023c). The same year, the government commissioned Statistics Sweden and Boverket to conduct an in-depth analysis of the conditions, needs and problems associated with exclusion in different areas (Government Offices of Sweden, 2023b). The stated purpose was to help authorities identify geographical areas where exclusion is particularly high, and where there are specific needs in terms of public sector initiatives.
The lessons learned from the Swedish Segregation Barometer offer valuable insights for the other Nordic countries. A key issue here is considering which conditions, needs and problems are most important to capture in different territorial contexts. While there are many similarities between the Nordic countries, there are also clear country-specific differences – capturing these should be one of the main starting points in developing a national-level tool elsewhere. Overall, the Segregation Barometer exemplifies the importance of data-driven approaches and collaborative efforts in addressing segregation.
4.5 Iceland
Historically, issues of exclusion and segregation have not been a political priority in Iceland, partly because Iceland’s levels of income inequality are among the lowest in Europe. Over the past two decades, however, the number of foreign-born people residing in Iceland has risen significantly, to the extent that the proportion of non-natives is among the highest in the Nordic countries (Heleniak, 2024).
These developments have led to growing signs of segregation in Iceland (Oddsson, 2022). In particular, increased diversity and a tightened housing market has led to limited affordable housing options, heightening the need for effective policies aimed at strengthening social inclusion and counteracting segregation. While there are currently few specific policies explicitly addressing segregation, a number of initiatives have sought to develop social cohesion- and equality-related indicators that can provide a more solid basis for supporting policy-making and planning.
With this in mind, this section explores various social indicators developed in Iceland for monitoring the health and social wellbeing of its population. This includes both national-level indicators and initiatives in the City of Reykjavík, where relevant indicators have been used to guide the planning and targeting of services.
4.5.1 Policies and plans
As already outlined in section 3.5, the issues of segregation, integration and inclusion have only fairly recently gained prominence on the policy agenda in Iceland. Nevertheless, several policies and plans relevant to spatial planning, integration, education, and housing already exist and more are in development, both at the national level and among municipalities. This is the case especially in Reykjavík, where the city has taken an active role in developing its own policies and plans for securing socially mixed, inclusive neighbourhoods.
From the perspective of using indicators to support policy actions, the governmental ‘Action Plan For Immigration Matters 2021–2024’ is a relevant document (Icelandic Government, 2022). Regarding social inclusion and segregation, the action plan focuses on the topic specifically from the perspective of immigration with possible future actions including the development of a platform that enables the sharing of relevant research, knowledge and statistical information. Given that Iceland does not yet have a formal policy on countering segregation and promoting social inclusion, no indicators on these specific topics currently exist. That said, some social wellbeing indicators are already available and will likely play a role in developing action plans going forward.
One initiative specified in the previously mentioned action plan involves establishing cooperation between two key governmental institutions – the Multicultural Centre and the Office of Equality – in order to support local authorities seeking to integrate multicultural policies and equality programmes. Many ministries, governmental institutions and municipal institutions are directly or indirectly involved in matters concerning segregation and social exclusion. At the state level, the most important actors are the Ministry of Social Affairs, Ministry of Finance and Economic Affairs, Ministry of Infrastructure, and Ministry of Education and Culture. Furthermore, the government tasks Statistics Iceland with gathering certain social indicators on its behalf.
At present, however, the indictors are employed purely as a monitoring tool, with the data yet to be used directly in policy development at either a state or municipal level. This may be set to change, given that the social indicators were purportedly developed not only to monitor the welfare of the population, but to inform policy-making and political decisions (Interview 5, 2023; Interview 19, 2023; Statistics Iceland, 2023).
4.5.2 Social indicators for measuring wellbeing
Although the social indicators gathered in Iceland have yet to be utilised in formulating or implementing specific social exclusion- and segregation-related policies, it is highly likely that they will come to play a vital role in the near future. The development of social indicators was initiated by the Icelandic government in 2009 following the international banking crisis, which hit Iceland particularly hard. Since 2012, the Ministry of Social Affairs and the Statistical Office of Iceland have collected and published annual measurements encompassing various factors intrinsic to people’s lives and their social wellbeing (Statistics Iceland, 2023). Social wellbeing is divided into 11 dimensions according to the classification used by various statistical offices and international organisations. Building on this, there were a total of 55 indicators used in Iceland’s first round of measurements, rising to a high of 67 in 2014, divided into the following categories: demographics, equality, sustainability, health and cohesion.
In 2015, under the Icelandic presidency of the Nordic Council of Ministers, a cross-Nordic project was established aimed at developing a national indicator system suitable for Nordic collaboration. The project was carried out in collaboration with NOSOSCO (Nordic Social-Statistical Committee) and NOMESCO (Nordic Medico-Statistical Committee). One important duty assigned to the project’s task force was reviewing relevant existing international methods and measurements. Having acknowledged that most of these existing indicator systems employ similar approaches, the project’s final report attempted to set out a range of indicators that would specifically address Nordic settings and challenges (Nyman et al., 2016).
The Icelandic social indicator system was subsequently developed using the final report as a frame of reference, with also taking into account the quality criteria set out by the Statistics Office of the European Union (Eurostat), as well as the Organisation for Economic Co-operation and Development (OECD)’s 2018 report on wellbeing (European Statistical System Committee, 2017; OECD, 2018). Since 2019, the Icelandic system has used 41 statistical parameters, defined and placed within the following 11 dimensions: 1) education; 2) employment; 3) work–life balance; 4) economy; 5) housing; 6) security; 7) wellbeing; 8) health; 9) social connections; 10) democracy; and 11) environmental quality (see Table 13) (Statistics Iceland, 2023).
While some indicators are still under development, most are published and can be viewed at the municipal level. In the case of the Reykjavík Capital Area, it is also possible to dig down to the district level. It should, however, be noted that many Icelandic municipalities have very few inhabitants, meaning municipal – and by extension sub-municipal – comparisons are often of little relevance. Data is collected and published annually, with the underlying notion being that it is important to consider various aspects of people’s situations beyond the financial when attempting to understand social wellbeing. In this context, the concept of welfare inequality – which assumes that inequality can exist in many different ways – is utilised (Statistics Iceland, 2023).
Table 13. Indicators gathered (or under development) by Statistics Iceland
Social dimension | Indicators |
Employment | NEET: Young people not in work, study or vocational training Unemployment: Percentage of unemployed in the labour force Employment: Ratio of labour force to the total population Long-term unemployment: Percentage of unemployed people who have been actively looking for a job for at least a year Outside the labour market: Percentage of people aged 16‒74 outside the labour market Those with limited work: Percentage of people in part-time jobs but want to work more |
Social connections | Social networking: Indicator under development Social support: Indicator under development Participation in social life: Indicator under development |
Economy | Properties: Average family assets Total revenue: Sum of employment income, capital income and other income Low-income ratio: Percentage of individuals with an income below 60% of the median disposable income Debts: Total family debt Lack of material quality: Percentage of households that lack certain material qualities Significant lack of material quality: Percentage of households living with a significant lack of material quality (defined as those that fall below the threshold of at least three of nine defined indicators, e.g. cannot meet unexpected expenses, cannot afford a car or a yearly week-long vacation) Financial aid recipients: Number of people receiving financial assistance from the municipality by family type Persistently low income: Indicator under development |
Health | People in good health: Percentage of people living in good health People with health restrictions: Percentage of people facing limitations in their daily life due to health conditions Refusal of health care due to cost: Percentage of people who refuse health care because of cost Denial of dental care due to cost: Percentage of people who refuse dental care because of cost |
Housing | Burdensome housing costs: Housing costs of at least 40% of household disposable income Poor condition of housing: Percentage of people who say they live with damp, mould and leaking roofs Cramped living: Proportion of people who live in cramped conditions Assessment of housing cost burdens: Percentage of people who say housing costs are a big burden Fallen behind on mortgage or rent: Percentage of people who have been unable to pay their mortgage or rent on time |
Work–life balance | Parental leave: indicator is under development Non-traditional working hours: Percentage of people working non-standard working hours Working hours per week: Number of working hours people report they have worked in their main and secondary jobs |
Democracy | Participation in parliamentary elections: Voter turnout by gender Participation in municipal elections: Ratio of votes cast to number of people on the electoral roll Trust in political parties: Indicator under development Confidence in parliament: Percentage of people with a lot of confidence in the Icelandic parliament (Alþingi) |
Education | Children in kindergarten: Number of children in kindergarten School attendance in secondary school: Percentage of students attending secondary school by age School attendance at university: Percentage of students attending university by age |
Security | Accidental deaths: People who have died from illness and accidents Security in the local environment: Percentage of people who experience crime in their local area |
Environment | Noise in the local environment: Percentage of people inconvenienced by noise in their local environment Pollution in the local environment: Percentage of people inconvenienced by dirt and pollution in their local environment |
Wellbeing | Adult happiness: Percentage of adults who rate their happiness at least 8 on a scale of 1–10 Life satisfaction: Indicator under development |
Source: Statistics Iceland, 2023
The list of indicators in Table 13 includes both quantitative indicators compiled by Statistics Iceland and more qualitative indicators taken from the yearly living standards study, also conducted by Statistics Iceland. The latter study (Statistics Iceland, 2023) has been carried out annually since 2004 using a sample of up to 5,000 people selected from the national register, and is part of the European Union’s coordinated living standards study. Participants are asked to participate for four years in a row, making it a longitudinal study capable of providing a broader picture of how living standards change over time and are distributed between different groups of people. Most of the study’s questions concern housing, finances, health and labour market status, with the resultant data providing an important source for the monitoring of social wellbeing.
In 2019, the first report providing a comprehensive statistical overview of immigrants in Iceland was published, focusing especially on the state of their finances, education, employment, housing, democracy, work–life balance, environmental quality and safety (Statistics Iceland, 2019b). While the report, which used social indicators and data dating back up to ten years, did provide new insights into the socio-economic conditions of immigrants, the information collected was less detailed compared to that gathered for Icelandic nationals. Moreover, wellbeing and social relationship indicators were not considered due to irregular measurements. Nonetheless, the report did reveal various disparities between immigrants and Icelandic nationals.
Among other things, the results showed that the majority of immigrants in Iceland are of working age and have been in the country for a relatively short period of time. They also tend to have a lower birth rate than Icelandic nationals and are predominantly male. Interestingly, most immigrants come from countries with good healthcare, education and financial systems. Overall, immigrants in Iceland have good access to the labour market and they are more likely to be overeducated compared to nationals. In addition, comparatively few immigrants have a higher total income than nationals. Also, the school attendance of immigrant students in secondary school at the age of 16 is lower than that of nationals – a gap that widens as they get older. Another observation was that immigrants are more likely than nationals to live in cramped conditions and be in a rented property (Statistics Iceland, 2019b).
Other research in Iceland has shown that immigrants tend to have less trust towards public institutions, including those relating to the labour market (Skaptadóttir et al., 2020), and that immigrants typically less engaged in Iceland’s civil society – for example, through participation in union activities and politics (Eythórsson & Gudmundsson, 2020).
One important issue relating to segregation, integration and social inclusion concerns the rental market for housing in Iceland, which is almost exclusively private and regarded as expensive, insecure and congested (Anundsen et al., 2021). The fact that Iceland’s population has grown significantly over the past decade – mainly due to immigration – has placed further strain on the housing market. Although Iceland has the highest share of owner-occupied dwellings among the Nordic countries, privately owned housing is far less common among immigrants than nationals (OECD, 2023).
Another point worth noting is that migration to Iceland, in contrast to the other Nordic countries, mainly consists of labour migrants. As such, the unemployment rate among immigrants has historically been relatively low – often lower than that of the native-born population before the COVID-19 pandemic (Sánchez Gassen et al., 2022)
In sum, with migrants now beginning to settle in Iceland in larger numbers, greater attention is being paid to questions of social inequality. This includes looking beyond the economy and employment to consider aspects such as social welfare, wellbeing, segregation and social inclusion. Although there are not yet indicators directly relating to these thematic areas in use when it comes to supporting policy and planning, initiatives to develop and incorporate such indicators are currently underway.
4.5.3 Reykjavík takes the lead
Although formal guidance or policies addressing segregation and social exclusion are lacking at the national level, these topics have gained greater prominence in a number of the City of Reykjavík’s policies and planning strategies. As discussed in section 3.5, Reykjavík has prioritised the development of socially mixed, inclusive neighbourhoods served by public transport and green-blue areas, where services and social institutions are in close proximity. Reykjavík’s master plan further states that social mixing and diversity should serve as a guiding principle when planning new neighbourhoods. More specifically, this means including housing for all social groups; that 25% of new apartments should be run by non-profit housing associations; and that special attention should be paid to the housing needs of young people and those entering the housing market for the first time (City of Reykjavík, 2020, 2022).
The City of Reykjavík has also done substantial work on integrating social inclusiveness into various plans and policies, both from the point of view of the organisation being an employer and a service provider. This can be seen, for example, in educational plans and cultural- and sports-related affairs, as well as policies relating to immigration and integration, social and educational policy, and human rights policy (City of Reykjavík, 2012, 2016, 2017c, 2021c).
Like at the national level, the City of Reykjavík’s segregation- and social inclusion-related policies tend to be sectoral plans, with the relevant topics integrated into various policy documents that serve to guide policy development. Again, given that there is no specific policy addressing segregation and social inclusion, indicators of these themes are not directly used in policy-making. Nevertheless, the administration does make use of indicators in targeting areas and neighbourhoods in need of particular attention.
Figure 13. Housing construction in central Reykjavík
Source: CC BY-SA 4.0, Yadid Levy, Norden.org
The relevant data reveals an uneven geographic distribution of population groups – based on socio-economic characteristics or proportion of people with a foreign background – across different neighbourhoods. In 2019, immigrants comprised 18.6% of Reykjavík’s overall population. However, in some neighbourhoods immigrants accounted for only 4% of the population, compared to 35% elsewhere (Statistics Iceland, 2020). Statistics such as these have been used on an informal basis to guide the planning of services, as needs can vary significantly from one place to another based on background, demographic and labour market characteristics (Slätmo et al., 2022, 2023). For example, such data has been used to identify where best to locate service centres, although this is not yet subject to a formal process, nor has the data made it into any official policy work as yet (Interview 20, 2023).
Nonetheless, there are expectations that many of the indicators already available or under development – such as those measuring more qualitative topics like social wellbeing, quality of life or social participation – will before long be used in a more formalised manner in planning, policy-making and implementation (Interview 5, 2023; Interview 6, 2023).
4.5.4 Key takeaways
Various societal changes have taken place in Iceland over the past two decades, as a result of which the issues of social inclusion and segregation have risen up the policy agenda. This can be observed at national level in the form of sectoral plans that indirectly address these issues, and in key education, equality and human rights legislation that imposes obligations on the state to combat segregation. In addition, more concrete initiatives linked to these policy themes are being pursued in Reykjavík and the wider Capital Area, especially in relation to developing more socially mixed, inclusive neighbourhoods. In the Capital Area, public transport infrastructure is also viewed as a means of increasing equality, reducing segregation and promoting diversity in urban development
In this context, Iceland has developed a comprehensive social indicator system that encompasses dimensions such as education, employment, housing, security, wellbeing, health, social connections, democracy, and environmental quality. While these indicators are not yet fully integrated into formal policies, they are nevertheless being increasingly used to assess people’s status and situation.
Going further than this, the City of Reykjavík is making strategic use of indicators to guide service planning and assess needs based on the demographic and socio-economic characteristics of different areas. Meanwhile, at the national level, policy attention is now shifting towards addressing social inequality, rather than simply dealing with economic factors. This is evidenced by the ongoing development of indicators concerning social wellbeing, quality of life and social participation.
Overall, Iceland finds itself having to navigate the challenges of increased diversity, housing shortages and the need for inclusive urban planning. In this respect, the development of social indicators reflects a commitment to better understanding the complex dynamics of social wellbeing, and in turn segregation and inclusion.